Developing a deep-learning-based diagnostic model demands extensive labor for medical image labeling. Attempts to reduce the labor often lead to incomplete or inaccurate labeling, limiting the ...
The in silico labeling prediction of organelle fluorescence from label-free microscopy images has the potential to revolutionize our understanding of cells as integrated complex systems. However, ...
If a team switches labeling tools mid-project or combines datasets labeled with different platforms, coordinate system mismatches produce bounding boxes that are wrong by design. The model trains on ...